Autonomous vehicles use various computing systems to aid in the transport of passengers from one location to another. Some autonomous vehicles may require an initial input or continuous input from an operator, such as a pilot, driver, or passenger. Other autonomous systems, for example autopilot systems, may be used only when the system has been engaged, which permits the operator to switch from a manual mode (where the operator exercises a high degree of control over the movement of the vehicle) to an autonomous mode (where the vehicle essentially drives itself) to modes that lie somewhere in between.
Such vehicles are typically equipped with various types of sensors in order to detect objects in the surroundings. For example, autonomous vehicles may include lasers, sonar, radar, cameras, and other devices which scan and record data from the vehicle's surroundings. These devices in combination (and in some cases alone) may be used to identify the shape and outline objects in a roadway and safely maneuver the vehicle to avoid the identified objects. This detection and identification is a critical function for autonomous vehicles but may be very difficult because the sensor data may include vast amounts of information. For example, laser sensors from a single autonomous vehicle may collect tens of thousands of data points off of a single object, such as another car. Processing such a large amount of data points in three dimensions is very time consuming and impractical for real time use of the data.